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The integration of seismic anisotropy and reservoir performance data for characterization of naturally fractured reservoirs using discrete feature network models

机译:使用离散特征网络模型整合地震各向异性和储层性能数据表征天然裂缝性储层

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摘要

This dissertation presents the development of a method for quantitative integration of seismic (elastic) anisotropy attributes with reservoir performance data as an aid in characterization of systems of natural fractures in hydrocarbon reservoirs. This new method incorporates stochastic Discrete Feature Network (DFN) fracture modeling techniques, DFN model based fracture system hydraulic property and elastic anisotropy modeling, and non-linear inversion techniques, to achieve numerical integration of production data and seismic attributes for iterative refinement of initial trend and fracture intensity estimates. Although DFN modeling, flow simulation, and elastic anisotropy modeling are in themselves not new technologies, this dissertation represents the first known attempt to integrate advanced models for production performance and elastic anisotropy in fractured reservoirs using a rigorous mathematical inversion. The following new developments are presented: .? Forward modeling and sensitivity analysis of the upscaled hydraulic properties of realistic DFN fracture models through use of effective permeability modeling techniques. .? Forward modeling and sensitivity analysis of azimuthally variant seismic attributes based on the same DFN models. .? Development of a combined production and seismic data objective function and computation of sensitivity coefficients. .? Iterative model-based non-linear inversion of DFN fracture model trend and intensity through minimization of the combined objective function. This new technique is demonstrated on synthetic models with single and multiple fracture sets as well as differing background (host) reservoir hydraulic and elastic properties. Results on these synthetic control models show that, given a well conditioned initial DFN model and good quality field production and seismic observations, the integration procedure results in convergence of both fracture trend and intensity in models with both single and multiple fracture sets. Tests show that for a single fracture set convergence is accelerated when the combined objective function is used as compared to a similar technique using only production data in the objective function. Tests performed on multiple fracture sets show that, without the addition of seismic anisotropy, the model fails to converge. These tests validate the importance of the new process for use in more realistic reservoir models.
机译:本文提出了一种将地震(弹性)各向异性属性与储层性能数据进行定量整合的方法的开发,以帮助表征油气藏天然裂缝系统。该新方法结合了随机离散特征网络(DFN)裂缝建模技术,基于DFN模型的裂缝系统水力特性和弹性各向异性建模以及非线性反演技术,从而实现了生产数据和地震属性的数值集成,从而可以迭代地细化初始趋势。和断裂强度估算。尽管DFN建模,流动模拟和弹性各向异性建模本身并不是新技术,但本文代表了首次尝试使用严格的数学反演方法将裂缝性油藏的生产性能和弹性各向异性先进模型进行集成的尝试。提出了以下新发展: ?通过使用有效的渗透率建模技术,对实际DFN裂缝模型的高档水力特性进行正向建模和敏感性分析。 。 ?基于相同DFN模型的方位变化地震属性的正向建模和敏感性分析。 。 ?开发生产和地震数据相结合的目标函数并计算灵敏度系数。 。 ?通过最小化组合目标函数,DFN断裂模型趋势和强度的基于迭代模型的非线性反演。这项新技术在具有单个和多个裂缝集以及不同背景(宿主)储层的水力和弹性特性的合成模型中得到了证明。这些综合控制模型的结果表明,给定条件良好的初始DFN模型以及良好的现场生产和地震观测结果,积分过程会导致具有单个和多个裂缝集的模型的裂缝趋势和强度都趋于一致。测试表明,与仅在目标函数中使用生产数据的类似技术相比,使用组合目标函数可加快单个裂缝的收敛速度。对多个裂缝集进行的测试表明,如果不添加地震各向异性,模型将无法收敛。这些测试验证了在更实际的油藏模型中使用新工艺的重要性。

著录项

  • 作者

    Will Robert A.;

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  • 年度 2004
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  • 原文格式 PDF
  • 正文语种 en_US
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